Body Surface Temperature Research Articles

Systematic Review and Meta-Analysis of Thermal Stress Assessment in Poultry Using Infrared Thermography in Specific Body Areas

Thermal stress is a health and welfare concern in the poultry industry. Poultry have specific thermoregulation strategies for heat stress (i.e., vasodilatation) or cold stress (i.e., vasoconstriction). Infrared thermal (IRT) analysis is a non-invasive temperature assessment technology with significant benefits compared to conventional temperature measurements, which are invasive and time-consuming. However, a wide range of IRT methodologies and equipment are used for temperature assessment in poultry. The aim of this study was to perform a systematic review and meta-analysis of IRT applications in poultry undergoing thermal stress. The bibliographic search yielded 17 records for qualitative synthesis and 10 for quantitative analysis. The results showed IRT is more commonly studied during heat stress than cold stress, and more research is being conducted on laying hens than other poultry species. Also, four body areas (parts of the head, body, face, and leg) were identified as common areas of interest for body surface temperature measurement. There is a clear thermoregulation response to thermal stress in poultry, with marked differences between featherless and feather-covered areas. IRT in poultry undergoing thermal stress has a good diagnostic value and represents an important welfare assessment tool for future research, particularly when combined with other welfare assessment methods.

Efficiency of infrared pyrometer and infrared thermography for assessing body surface temperature in hair sheep

The objectives of this study were: (i) to verify and compare the coat surface temperature (CST) of regions of interest (ROI) measured through infrared pyrometer (IRP) and thermography (IRT) under two environmental conditions, to evaluate (ii) reliability and (iii) sensitivity of the two infrared equipments to the environmental effect. Twenty hair ewes (Ovis aries), multiparous, non-lactating, non-pregnant, with body weight 59.38 ± 6.23 kg and body score condition ranging from 2.5 to 4.5 were evaluated. All CST, in both infrared methods, were higher (P < 0.001) in the afternoon (2 to 3 p.m.), with the exception of eyes surface temperature (TSEY) from IRT, which was higher (P < 0.001) in the morning (8 to 9 a.m.). Regarding the infrared methods at different times (twice a day, morning and afternoon), of the day, CST values for all ROIs were significantly higher (P < 0.001) in thermography, regardless of the time shift, except for ear pinna surface temperature (TSE) and rectum surface temperature (TSR), which showed no significant difference (P > 0.05) between the infrared methods during the morning shift. The thermal environment significantly influences (P < 0.001) the surface temperature of various anatomical regions in both infrared methods. The correlation coefficients between IRT and IRP were moderate. The IRT is more sensitive to the thermal environment, as it presented higher canonical coefficients in the environmental variables. Among surface temperatures, eye surface temperature is the most influenced by variables in the thermal environment, especially THI. All three methods (digital thermometer-DT, IRT and IRP) showed >80 % of the data variation in the first two components. Using the DT, we observed an association between vaginal temperature (VT) and RT with air temperature (AT) and temperature humidity index (THI), which was similar to the infrared thermography pattern, in which all ROIs were highly correlated with AT and THI. The opposite was observed in the pyrometer, in which an association between eye temperature and RH and lower factor loadings of the other ROIs with AT and THI in the first component was observed. In conclusion, while IRP and IRT showed similar performance in the morning, IRT proved to be more accurate in the afternoon, demonstrating a higher success rate in classifying the group of origin. Therefore, it is concluded that IRT is more reliable than IRP in detecting surface temperature changes under high temperatures.

Evaluating the efficacy of probiotics and ascorbic acid as anti-stress agents against heat stress in broiler chickens.

Heat stress poses a substantial challenge to poultry production worldwide, highlighting the urgent need for effective management strategies. This study investigated the efficacy of probiotics (Saccharomyces cerevisiae) and ascorbic acid as antistress agents using cloacal and body surface temperatures (CT and BST) as heat stress biomarkers in broiler chickens. A total of 56 broiler chicks were used for the experiment and were divided into four distinct groups: control, probiotics (1 g/kg of feed), ascorbic acid (200 mg/kg of feed) and the combination of probiotics and ascorbic acid (1 g/kg and 200 mg/kg of feed, respectively). The study lasted 35 days; measurements were taken for ambient temperature (AT), CT, and BST. The ambient temperature in the pens consistently exceeded the thermoneutral zone (TNZ) established for broiler chickens. The CT values for broiler chickens in the probiotic group were significantly lower (p < 0.05) compared to the control group. Additionally, the BST values in the probiotic and probiotic + ascorbic acid groups were significantly lower (p < 0.05) than those in the control group. The findings suggest that incorporating probiotics, with or without ascorbic acid, can effectively reduce CT and BST values in broiler chickens thereby, enhancing thermoregulation when compared to the control group. This implies that using probiotics in poultry diets may enhance health and growth performance, potentially leading to better feed efficiency and reduced reliance on antibiotics. Implementing these dietary strategies could improve the productivity and welfare of broiler chickens in commercial settings.

PRELIMINARY DATA ON COAT COVERAGE AND GROOMING INTERFERING WITH THE THERMAL COMFORT OF LHASA APSO AND SHIH TZU DOGS

The objective of this report was to investigate the effects of grooming on thermal comfort in Lhasa Apso and Shih Tzu dogs exposed to different ambient temperatures. A randomized block design in a 3 x 2 factorial scheme was used, with 3 different temperatures associated with whether the animal was groomed or not. Six adult dogs, consisting of two Lhasa Apsos and four Shih Tzus, were used. The dogs were exposed to temperatures of 17°C, 25°C, and 33°C both before and after grooming. Physiological parameters (blood pressure, heart rate, respiratory rate, rectal temperature, ambient temperature, ITU, and body surface temperature) were measured using infrared thermography with a portable IRT camera. The images were analyzed using FLIR Tools™ software with an emissivity of 0.97. Variance analysis was performed to evaluate the isolated effects and interactions between the factors of coat coverage and ambient temperature at the 5% significance level. No interaction was found between the treatments, nor were there isolated effects of the factors on the physiological parameters evaluated. A temperature of 33°C was associated with a higher rectal temperature (p&lt;0.05) in the animals. Ungroomed dogs exposed to temperatures of 25°C and 33°C had ITU values above the thermal comfort limit. In terms of body temperature, there was a significant interaction effect between coat coverage and the environment under different climatic conditions (p&lt;0.05). The surveyed grooming dogs exhibited greater body temperatures at all temperatures tested, namely, 17°C, 25°C, and 33°C. Grooming did not reduce the effects of thermal stress caused by different climatic conditions, indicating that grooming is not advisable for these animals

A two-parameter Tikhonov regularization for a fractional sideways problem with two interior temperature measurements

This paper deals with a fractional sideways problem of determining the surface temperature of a heat body from two interior temperature measurements. Mathematically, it is formulated as a problem for the one-dimensional heat equation with Caputo fractional time derivative of order α∈(0,1], where the data are given at two interior points, namely x=x1 and x=x2, and the solution is determined for x∈(0,L),0<x1<x2≤L. The problem is challenging since it is severely ill-posed for x∉[x1,x2]. For the ill-posed problem, we apply the Tikhonov regularization method in Hilbert scales to construct stable approximation problems. Using the two-parameter Tikhonov regularization, we obtain the order optimal convergence estimates in Hilbert scales by using both a priori and a posteriori parameter choice strategies. Numerical experiments are presented to show the validity of the proposed method.

Thermal radiation imaging technology and sensor assisted calculation of sports training technology simulation

With the development of sports training science and technology, the real-time monitoring of athletes’ physical condition and training effect is becoming more and more important. As a non-contact measurement method, thermal radiation imaging technology can capture the changes of athletes’ body surface temperature efficiently and in real time, and provide relevant information about physiological state and performance indicators. This paper discusses the application of thermal radiation imaging technology in sports training to help measure athletes’ physical state and training effect, so as to provide scientific basis for improving training efficiency and reducing sports injuries. In this paper, the high resolution thermal imaging equipment is used to systematically analyze the thermal radiation imaging of athletes, and the physiological index monitoring and data processing technology are combined to dynamically observe the temperature distribution and change characteristics of athletes under different training states. Through comparative analysis, the correlation between the data provided by thermal radiation imaging technology in the training process and the traditional physiological indicators was evaluated. The results show that thermal radiation imaging technology can effectively reflect the heat distribution and local body temperature changes of athletes during training. Compared to traditional physiological feedback data, the technology has significant advantages in quickly identifying excessive fatigue and potential injuries in athletes, especially during high-intensity training, and can provide early warning of associated risks. The application of sensor-assisted measurement system will further enhance the accuracy and effectiveness of sports scientific research and provide important support for athletes’ scientific training and health management.

Adaptive capability of slow-growing backyard poultry as indicated by physiological and molecular responses in a hot and humid coastal climate

Assessing the adaptability of slow-growing rural chickens for improving thermotolerance to suit the global climate change is a major research need. This work was aimed to evaluate the adaptability of CARI-Debendra chickens and to identify the polymorphism as well as expression profiling of thermotolerant genes (HSP70 and GRP78) under prevailing temperature-humidity indices and thermal stress in a coastal environment. One hundred sixty straight run chicks were reared at THI≥75 (control) and THI>80 under coastal climate till 12 weeks. Polymorphism of HSP70 and GRP78 candidate genes were explored using restriction enzymes TaqI and HaeIII to identify possible thermotolerance markers. Expression profiling of both the genes in liver, intestine and pectoralis muscle was determined through quantitative real-time PCR. Rectal and body surface temperature recorded in the neck and back showed significant differences (P < 0.01) with higher temperature in THI>80 group. Comparatively lower live weights (P < 0.05) and poor FCR were recorded in THI>80 group. The villi height in all intestinal segments was significantly lower (P < 0.01), but deeper crypt depth was observed in THI>80 than control group. A lowest thymus weight (P < 0.05) was noted with no significant differences in immune response in treatment group. Serum levels of cholesterol, activities of lactate dehydrogenase, creatinine kinase and concentration of potassium, sodium and thyroxine hormone were not different between the 2 groups. The concentration of triiodothyronine and chloride ion was lower in THI>80 group indicating adaptive changes for thermoregulation. HSP70 gene expressions in the three tissues were differentially increased (P < 0.01) by temperature-humidity indices, but the expression of GRP78 was not different between the 2 groups. The results concluded that the environmental factors interact with genetics on adaptability towards thermotolerance in slow-growing chickens.

Thermal response in Boer goats differing in coat colour

Context The coat is the first defense layer protecting animals from direct sunlight, influencing radiant-heat absorption and loss. Dark coat colour may increase animal heat impact because of higher absorption of solar radiation. Aims We investigated the impact of pigmentation intensity on the heads of animals and their thermal responses to solar radiation. Furthermore, we compared the thermal responses between dark and light brown-coloured animals, to determine whether the duration of sun and shade exposure (3 h each) is sufficient to differentiate the heat gain and losses between the two groups. Methods The effect of coat colour on rectal and surface temperatures in Boer goats, classified according to their head pigmentation pattern as dark (DB, N = 11) or light brown (LB, N = 11), exposed to sun and shade, was evaluated. The animals’ body and head surface temperatures were measured the same day before, during, and after sun exposure by using infrared thermography. Individual thermographic images were analysed by body regions (rump, leg, neck) and head areas (eye, ear, upper and lower part of the head, and the muzzle). Key results During solar radiation, all measured variables increased. In the shade, the rump, leg, and neck surfaces remained elevated, whereas the head area cooled down faster, with the highest temperature changes measured for the ear of about 10%. Most surface cooling occurred within 30 min after returning to the shade. Coat colour groups differed only in higher overall muzzle temperature of DB than that of LB goats (P = 0.048). Correlations between rectal and surface temperatures were low to medium, ranging from −0.02 (eye) to 0.31 (muzzle). Conclusions The head area is suggested as the important thermal window for heat dissipation and selective brain cooling. Light brown-headed animals were more efficient in eliminating the heat gained from solar radiation when returned to shade. Implications The colouration of the animal’s head may play an important role for its heat tolerance. As an easy-to-recognise characteristic, coat colour can serve as a selection trait for local goat populations. In view of global warming, selection for lighter coat colour in domestic ruminants may also become important even under temperate climates.

Predictive models for heat stress assessment in Holstein dairy heifers using infrared thermography and machine learning.

Heat stress is a condition that impairs the animal's productive and reproductive performance, and can be monitored by physiological and environmental variables, including body surface temperature, through infrared thermography. The objective of this work is to develop computational models for classification of heat stress from respiratory rate variable in dairy cattle using infrared thermography. The database used for the construction of the models was obtained from 10 weaned heifers, housed in a climate chamber with temperature control, and submitted to thermal comfort and heat wave treatments. Physiological and environmental data were collected, as well as thermographic images. The machine learning modeling environment used was IBM Watson, IBM's cognitive computing services platform, which has several data processing and mining tools. Classifier models for heat stress were evaluated using the confusion matrix metrics and compared to the traditional method based on Temperature and Humidity Index. The best accuracy obtained for classification of the heat stress level was 86.8%, which is comparable to previous works. The authors conclude that it was possible to develop accurate and practical models for real-time monitoring of dairy cattle heat stress.

Mask R-CNN and Centroid Tracking Algorithm to Process UAV Based Thermal-RGB Video for Drylot Cattle Heat Stress Monitoring

This study developed and evaluated an algorithm for processing thermal-RGB video feeds captured by an unmanned aerial vehicle (UAV) to automate heat stress monitoring in cattle housed in the drylots. The body surface temperature (BST) of individual cows was used as an indicator of heat stress. UAV data were collected using RGB and thermal infrared imagers, respectively, at 2 and 6.67 cm per pixel spatial resolution in Spring 2023 (dataset-1) and Summer 2024 (dataset-2). Study sites were two commercial drylots in Washington State. The custom algorithms were developed to: (1) detect and localize individual cows using a Mask R-CNN-based instance segmentation model combined with centroid tracking; and (2) extract BST by averaging the thermal-imagery pixels for each of the segmented cows. The algorithm showed higher detection accuracy with RGB images as input (F1 score: 0.89) compared to thermal (F1 score: 0.64). BST extraction with combined RGB and thermal imaging approach required corrections for alignment problems associated with differences in optics, imaging field of view, resolution, and lens properties. Consequently, thermal imaging-only approach was adopted for assessing real-time cow localization and BST estimation. Operating at one frame per second, algorithm successfully detected 72.4% and 81.65% of total cows in video frames from dataset-1 (38 s) and -2 (48 s), respectively. The mean absolute difference between algorithm output and ground truth (BSTGT) was 2.1 °C (dataset-1) and 3.3 °C (dataset-2), demonstrating satisfactory performance. With further refinements, this approach could be a viable tool for real-time heat stress monitoring in large-scale drylot production systems.

143 Short- and long-term effects of heat stress in cow-calf pairs adapted to tropical and subtropical regions

Abstract Chronic exposure to high temperatures and humidity can limit beef cattle performance in tropical/subtropical environments, regardless of breed. Despite better heat adaptability compared with Bos taurus cattle, heat-stressed Bos indicus cattle also experience an increase in body temperature above the physiological limit. As body temperature increases, cascades of behavioral and physiological events are triggered to lessen heat load but often at the expense of productive outcomes. Contrary to other species and feedlot beef cattle, the effects of heat stress on physiology and performance of grazing cow-calf pairs have not been evaluated in detail, particularly for Bos indicus cattle. Preliminary data showed opposite outcomes to heat stress in Bos indicus vs. Bos taurus cattle, limiting the implications of the existing data generated from studies using beef and dairy Bos taurus cattle. This presentation will share some nutritional and management practices to mitigate heat stress in grazing beef cattle. Practices mentioned herein include altering the timing of body weight (BW) growth pattern (stair-step, SST) and immunomodulatory feed ingredient (IFI) supplementation for replacement beef heifers, and maternal access to shade to reduce heat load. For 100 d before the breeding season, Bos indicus-influenced beef heifers grazing warm-season grasses received a constant supplementation amount or SST strategy (50 d of low then 50 d of high supplementation), with or without IFI. Under severe heat stress conditions, IFI supplementation reduced heifer vaginal temperature but did not increase their growth and reproduction, whereas the SST strategy lowered internal body temperature, enhanced growth performance and pregnancy success compared with a conventional constant supplementation practice. Our group is also focused on the critical need to determine the specific effects of heat stress mitigation during pre- and postnatal phases on physiology and performance of Bos indicus-influenced cow-calf pairs. Study 1 evaluated the impacts of maternal access to artificial shade from 83 d prepartum until 50 d postpartum on body thermoregulation, performance, and physiology of beef heifers and their first offspring. Removing maternal access to shade led to greater maternal respiration rate, vaginal and body surface temperatures and reduced maternal body condition score and calf BW at birth. Nonetheless, offspring born from cows with no access to shade were remarkably heavier during a 60-d post-weaning period and had decreased plasma indicators of inflammation and positive effects to humoral immune response. Study 2 is a multi-year, USDA/NIFA-funded study designed to capitalize on the ability of cattle to reprogram physiological/immunological systems following exposure to stress during gestation. Study 2 combined gestational and postnatal heat abatement to enhance the overall growth/immune/reproductive performance of grazing Bos indicus-influenced cow-calf pairs. Partial data on long-term growth and reproductive performance, physiology, metabolome, and microbiome of both cows and their female offspring will be shared in this presentation.

Zero-shot image segmentation for monitoring thermal conditions of individual cage-free laying hens

Body temperature is a critical indicator of the health and productivity of egg-laying chickens and other domesticated animals. Recent advancements in thermography allow for precise surface temperature measurement without physical contact with animals, reducing animal stress from human handling. Gold standard temperature analysis via thermography requires manual selection of limited points for an object of interest, which could be time-consuming and inadequate for representing the comprehensive thermal profile of a chicken’s body. The objective of this study was to leverage and optimize a zero-shot artificial intelligence technology for the automatic segmentation of individual cage-free laying hens within thermal images, providing insights into their overall thermal conditions. A zero-shot image segmentation model (Segment Anything, “SAM”) was modified by replacing manual selections of target points with automatic selection of the initial point using pre-processing techniques (e.g., thresholding) in each thermal image. The model was also incorporated with post-processing techniques integrated with a machine learning classifier to improve segmentation accuracy. Three versions of modified SAM models (i.e., SAM, FastSAM, and MobileSAM), two common instance segmentation algorithms (i.e., YOLOv8 and Mask R-CNN), and two foundation segmentation models (i.e., U2-Net and ISNet) were comparatively evaluated to determine the optimal one for bird segmentation from thermal images. A total of 1,917 thermal images were collected from cage-free laying hens (Hy-Line W-36) at 77–80 weeks of age. The image dataset exhibited considerable variations such as feathers, bird movement, body gestures, and the specific conditions of cage-free facilities. The experimental results demonstrate that the modified SAM did not only surpass the six zero-shot models—YOLOv8, Mask R-CNN, FastSAM, MobileSAM, U2Net, and ISNet—but also outperformed other modified SAM-based models (Modified FastSAM and Modified MobileSAM) in terms of hen detection performance, achieving a success rate of 84.4 %, and in segmentation performance, with an intersection over union of 85.5 %, recall of 91.0 %, and an F1 score of 92.3 %. The optimal model, modified SAM, was pipelined to extract statistics including the averages (°C) of mean (27.03, 27.04, 28.53, 26.68), median (26.27, 26.84, 28.28, 26.78), 25th percentile (25.33, 25.61, 27.26, 25.53), and 75th percentile (28.04, 27.95, 29.22, 27.55) of surface body temperature of individual laying hens in thermal images for each week. More statistics of hen body surface temperature can be extracted based on the segmentation results. The developed pipeline is a useful tool for automatically evaluating the thermal conditions of individual birds.

The back body temperatures of patients with idiopathic scoliosis measured through exercise.

Aerobic exercise is closely associated with the vital functions of patients with scoliosis. Infrared thermography (IRT) has been increasingly applied in physiological measurements in recent years. This observational study aimed to use IRT to examine the back body surface temperatures of patients with idiopathic scoliosis during aerobic exercise. Forty-two participants who completed a pre-test were divided into a scoliotic group and a non-scoliotic group. Both groups completed a 30-minute cycling exercise, during which their back body temperature was measured using IRT, and the root-mean-square of the back electromyography value after 30minutes of aerobic exercise was analyzed. The back body temperature decreased significantly after 30minutes of exercise in the non-scoliotic group. In contrast, the back body temperature (at the trapezius and quadratus lumborum muscles) was asymmetric or increased after exercise in the scoliotic group. These findings suggest that when patients with scoliosis exercise, their back body temperature should be assessed thoroughly to prevent adverse physiological reactions potentially caused by back body temperature imbalances as well as the potential health problems caused by poor heat dissipation. In addition, such observations can be useful in the early screening of scoliosis.

Profiling the dynamic variations in body and scrotal surface temperatures of goats reared under stressful conditions using infrared thermography: Analytical perspectives

Infrared thermography (IRT) is an essential non-invasive method for analyzing surface temperature variations in animals, offering valuable insights into livestock stress responses. Despite their resilience, goats can face significant challenges under extreme conditions like heat-stress and water deprivation. This experiment aimed to delineate the dynamic variations in whole-body and scrotal surface temperatures in goats subjected to the combined impact of both conditions using IRT. Eight healthy Aardi bucks were exposed to three 72-h treatments: euhydration, dehydration, and rehydration. Continuous meteorological monitoring provided ambient-temperature, relative-humidity, and temperature-humidity index (THI) values. Surface temperatures were measured twice daily at 08:00 and 15:00, and thermal gradients between ambient and body or scrotal surface temperatures were computed. Based on the obtained mean THI values, the bucks experienced heat-stress throughout the experiment. Additionally, results revealed noticeable variations in both surface temperatures across treatments and time points, indicated by measures of central tendency, variability, shape descriptors, and frequency distribution of temperature. Morning measurements indicated lower temperatures and gradients under euhydration, while water deprivation led to higher temperatures and compromised thermal regulation. Conversely, afternoon data showed higher variability in temperature responses, highlighting the compounded effect of diurnal heat-stress and water deprivation. Although water-restoration mitigated some effects of deprivation, it did not fully restore thermal homeostasis to euhydrated levels. Thermal gradients further emphasized the goats' dynamic thermoregulatory mechanisms, which were compromised under water deprivation, particularly in the scrotal region, but were partially restored upon restoration. These findings demonstrate the effectiveness of IRT in assessing thermal responses in goats and underscore the importance of adequate hydration for maintaining thermal balance under heat-stress. The herein performed profiling provides valuable insights with implications for overall health, reproductive efficiency, productivity, and welfare in heat-stressed and water-deprived goats, which might offer a framework for future research on livestock adaptation to such challenging environmental conditions.

Enhancing stress assessment in sledge reindeer (Rangifer tarandus): a pilot study on infrared thermal imaging and its opportunities for advancement as a welfare assessment tool

Measuring immediate physiological stress responses in animals can be challenging; saliva and blood sampling, while invasive, may also generate confounding stress responses, and equipping animals with heart rate sensors is not always feasible. Nevertheless, emerging technologies offer a non-invasive and contactless method to measure additional body surface temperature changes induced by acute stress, using infrared thermal measurement of the eye caruncle region. Contactless temperature measurement has the potential to assess the emotional state of animals affected by human physical contact. Reindeer, being highly sensitive to touch and naturally avoiding physical contact, exemplify this case. With growing interest in safari tours involving sledging reindeer, there is a need to investigate how these animals are affected by human interactions and how they adapt to daily close contact. In this pilot experiment, we evaluated the efficacy of thermal imaging in measuring medial canthus temperature fluctuations in non-habituated sledging reindeer while being petted by unfamiliar humans. Our findings support the hypothesis that medial canthus temperature significantly decreases during petting and increases once the interaction ceases, aligning with established stress response patterns found in the literature. This pilot experiment underscores the potential of infrared thermal imaging for non-invasively monitoring physiological responses to stress in tamed reindeer. Moreover, it sets the foundation for refining methodologies and experimental designs using infrared thermal imaging in animal welfare research.

Impact of greenery and waterbody on the cooling of city’s environment: a case of Rajshahi City

ABSTRACT Both plants and bodies of water are crucial to the health of the urban landscape. The degree to which these factors contribute to cooling appears, however, to change depending on factors such as location, time of year, and the mix of land use and land cover. The purpose of this study was to investigate the potential role of trees and water in Rajshahi City Corporation in reducing urban heat island effect. As a first step, satellite images are processed to generate the normalized difference vegetation index (NDVI) and the modified normalized difference water index (MNDWI). The second step is to produce maps of vegetation and water features by using a decision tree (DT) algorithm fed with threshold values from the indices. After that, thermal bands from the Landsat 8 OLI and MODIS Terra Earth observation data are used to create a map of the land surface temperature (LST). Finally, this study assessed the effect of vegetation and water coverage on global surface temperatures by analyzing their spatial distributions. Different kinds of land cover can be found in and around urban centers. Therefore, this study chose two types of water bodies (big and small) and two types of vegetation (sparse and attached/compact) for experiment. Water bodies produce cooler temperatures than other land cover types, as shown by the data. It has been found, however, that cooling rates differ across large and small bodies of water. The surface temperatures of large bodies of water are typically lower than those of smaller bodies of water. Accordingly, it appears that expansive areas significantly impact the cooling of metropolitan environments. The findings also demonstrate a difference in surface temperature between areas of dense and sparse vegetation. The cooling impact of the sparse vegetation is much less than that of the dense and widespread vegetation. There was a significant relationship between surface warming and vegetation cover in this study (R2 = 0.81). Contrarily, the presence of water and vegetation is strongly correlated (R2 = 0.88) with surface warming. The findings also show that surface warming differs depending on land use. According to a study of four typical RCC locations, business districts and industrial zones have a far greater impact on local surface temperatures than do residential developments. The experiment demonstrates that the residential area with a high proportion of vegetation had a lower average temperature by nearly 2°C. The study’s findings highlight the value of maintaining urban parks and water features.

Using Thermal Signature to Evaluate Heat Stress Levels in Laying Hens with a Machine-Learning-Based Classifier.

Infrared thermography has been investigated in recent studies to monitor body surface temperature and correlate it with animal welfare and performance factors. In this context, this study proposes the use of the thermal signature method as a feature extractor from the temperature matrix obtained from regions of the body surface of laying hens (face, eye, wattle, comb, leg, and foot) to enable the construction of a computational model for heat stress level classification. In an experiment conducted in climate-controlled chambers, 192 laying hens, 34 weeks old, from two different strains (Dekalb White and Dekalb Brown) were divided into groups and housed under conditions of heat stress (35 °C and 60% humidity) and thermal comfort (26 °C and 60% humidity). Weekly, individual thermal images of the hens were collected using a thermographic camera, along with their respective rectal temperatures. Surface temperatures of the six featherless image areas of the hens' bodies were cut out. Rectal temperature was used to label each infrared thermography data as "Danger" or "Normal", and five different classifier models (Random Forest, Random Tree, Multilayer Perceptron, K-Nearest Neighbors, and Logistic Regression) for rectal temperature class were generated using the respective thermal signatures. No differences between the strains were observed in the thermal signature of surface temperature and rectal temperature. It was evidenced that the rectal temperature and the thermal signature express heat stress and comfort conditions. The Random Forest model for the face area of the laying hen achieved the highest performance (89.0%). For the wattle area, a Random Forest model also demonstrated high performance (88.3%), indicating the significance of this area in strains where it is more developed. These findings validate the method of extracting characteristics from infrared thermography. When combined with machine learning, this method has proven promising for generating classifier models of thermal stress levels in laying hen production environments.

Measurement of microclimates in a warming world: problems and solutions.

As the world warms, it will be tempting to relate the biological responses of terrestrial animals to air temperature. But air temperature typically plays a lesser role in the heat exchange of those animals than does radiant heat. Under radiant load, animals can gain heat even when body surface temperature exceeds air temperature. However, animals can buffer the impacts of radiant heat exposure: burrows and other refuges may block solar radiant heat fully, but trees and agricultural shelters provide only partial relief. For animals that can do so effectively, evaporative cooling will be used to dissipate body heat. Evaporative cooling is dependent directly on the water vapour pressure difference between the body surface and immediate surroundings, but only indirectly on relative humidity. High relative humidity at high air temperature implies a high water vapour pressure, but evaporation into air with 100% relative humidity is not impossible. Evaporation is enhanced by wind, but the wind speed reported by meteorological services is not that experienced by animals; instead, the wind, air temperature, humidity and radiation experienced is that of the animal's microclimate. In this Commentary, we discuss how microclimate should be quantified to ensure accurate assessment of an animal's thermal environment. We propose that the microclimate metric of dry heat load to which the biological responses of animals should be related is black-globe temperature measured on or near the animal, and not air temperature. Finally, when analysing those responses, the metric of humidity should be water vapour pressure, not relative humidity.

Characterization of the Temperament and Reactivity of Nelore Cattle (Bos indicus) Associated with Behavior Scores during Corral Management in the Humid Tropics.

The evaluation of the reactivity and distress of cattle during corral management, by means of subjective scores, aims at the standardization of behavioral indicators, through non-invasive methods, in addition to enabling the development of more appropriate management practices, thus promoting the comfort and well-being of these animals. Therefore, in this study, we aimed to characterize the temperament and distress of cattle managed in a corral using behavioral indicators during the rainiest period. For this, the experiment was conducted on a property located in the municipality of Mojuí dos Campos, during the rainiest quarter (February-April). Thus, 30 male cattle, not castrated, approximately 29 months of age, clinically healthy, and weighing 310 + 20 kg, were divided into three rearing systems: silvopastoral (SP), traditional (SS), and integrated (SI) systems. There were 10 animals per system. Physiological parameters were collected to evaluate rectal temperature (RT) and respiratory rate (RR), as well as body surface temperature (BST), through thermal windows (head and flank infrared temperature and rump infrared temperature). To evaluate temperament and reactivity, scores indicative of corral behavior were used, namely escape speed (ES), tension score (SS_1), tension score (SS_2), reactivity scale (RS), movement score (MS), and temperament scale (TS). The results showed that there was a thermal amplitude of 5.9 °C on average and 8.6 °C at maximum when comparing the structure of the corral and the trees. In addition, the comparisons between the production systems for the behavioral variables did not differ at the 5% significance level, except for ES, where the traditional system differed from the integrated system and the silvopastoral system, showing intermediate average values for both. In addition, there was a positive correlation between the variables RT and RR (r = 0.72; p < 0.01), RR and SS_2 (r = 0.38; p = 0.04), flank infrared temperature and MS (r = 0.47; p = 0.01), rump infrared temperature and RS (r = 0.37; p = 0.04), SS_1 and RS (r = 0.41; p = 0.02), SS_1 and SS_2 (r = 0.39; p = 0.03), RS and SS_2 (r = 0.58; p = 0.00), RS and MS (r = 0.50; p = 0.01), RS and TS (r = 0.61; p = 0.00), SS_2 and MS (r = 0.51; p = 0.00), SS_2 and TS (r = 0.47; p = 0.01), and MS and TS (r = 0.44; p = 0.02), and a negative correlation between ES and TS (r = -0.42; p = 0.02). The rainy season had a major influence on the evaluation of temperature and distress levels during handling in the corral, as evidenced by the association between physiological and behavioral parameters.

Application of thermography in the assessment of physical effort on body surface temperature distribution in racehorses

The aim of this study was to evaluate the efficacy of thermography in assessing the impact of regular physical effort on changes in the body surface temperature of the upper body parts of young racehorses. The study involved monitoring 33 racehorses aged 3 years in 3 imaging sessions over a period of 3 months. Temperature measurements of the neck and upper part of the forelimbs and hindlimbs from both sides were taken just before and after training. Three regions of interest (ROIs) located at the base of the neck, elbow and quarter on both sides of the body were analysed. Before physical effort, the average temperatures in all ROIs did not differ significantly between the right and left side of the body. After physical effort average surface temperatures of the left side of the elbow and quarter were significantly higher compared to the opposite side and the temperature at the base of the neck was higher on the right side in comparison to the left side (p&amp;lt;0.001). Body surface temperatures of all ROIs after physical effort significantly (p≤0.001) increased, with the greatest increase observed in the elbow (4.7°C) and the lowest in the base of the neck (3ºC). All regions demonstrated a positive correlation between average surface temperatures on the left and right side of the body, before and after training. There was a strong positive correlation between the average temperatures in the analyzed ROIs after physical effort with the strongest correlation between the elbow and quarter (r=0.773) and the weakest between the quarter and base of the neck (r=0.474). In conclusion, our study revealed that thermography remains a feasible diagnostic modality for identifying changes in upper parts of the body in response to physical effort and can therefore provide valuable insights into the assimilation of training regimes by the equine physiology.